The area under the ROC curve for the ACE-III diagnostic variable had a high value (AUC = 0.920 ± 0.014). A cut-off point of 81 points was suggested for ACE-III; the M-ACE diagnostic variable had an equally high value (AUC = 0.891 ± 0.017). A cut-off point of 20 points was suggested. A significant decrease in the mean score values for people who scored norm or below the norm under ACE-III, as compared to the MMSE results for norm (p < 0.0001), occurred for speech fluency (which decreased by 26.4%). The tests in question are characterised by high sensitivity and specificity. Targeted ACE-III seems best recommended for use in specialised diagnostic centres, whereas M-ACE appears to be a better suited diagnostic alternative for primary health care centres in comparison to MMSE.The research aims to compare the accuracy of the mini-mental state examination (MMSE), the Addenbrooke’s cognitive examination III (ACE-III) and the mini-Addenbrooke’s cognitive examination (M-ACE) within the Polish population. The model comprised several stages: the features of each test were compared; the shifts in result categorisations between the norm and below the norm were analysed; a third category—mild cognitive impairment (MCI)—was included. Additionally, particular ACE-III domains that scored below domain-specific norm thresholds were analysed to establish the potential early predictors of dementia. All tests correlated to a high and very high degree—cf. MMSE and ACE-III ( Early diagnosis of cognitive disorders in older people is a prerequisite for any therapy and activation programmes. The American Academy of Neurology recently recommended annual tests for cognitive disorders in patients above 65 who are under neurological care . AdditioThe World Health Organization are currently working on their own recommendations; however, all the documents published so far stress the validity of annual cognitive tests in people 65+ as part of primary health care services. Still, there has been no binding statement as to actual recommendations . Poland A noteworthy 2019 Cochrane review defines the current meta-analysis, which pertains to methods currently used in detecting dementia and MCI, namely, Addenbrooke’s cognitive examination-III (ACE-III) and mini-Addenbrooke’s cognitive examination (M-ACE/Mini-ACE) . The folApplying ACE-III as a screening method and a useful tool in the differential diagnosis of dementia variants has been researched frequently. Sitek et al.  presenteIn people with episodic memory disorders, especially in postponed reproduction, and semantic memory disorders (speech fluency and naming test), there may occur amnesic MCIs with a tendency towards AD convergence .M-ACE, on the other hand, is a short version of ACE-III. To verify its validity, there were 242 participants tested, including 28 with a recognised form of Alzheimer’s disease, 23 with a behavioural variant of frontotemporal dementia, 82 people with primary progressive aphasia, 21 with cortico-basal dementia and 78 people in a control group. According to Sitek et al. , the tesWSWOP Hospicjum Domowe in Poznań, Poland, or volunteered to take part in activation programmes for older adults and underwent cognitive screening as part of the project’s diagnostic procedure.The study was conducted from 2015 to 2018. Participants were referred for a psychological test by a geriatrician or other specialist residing at the geriatric health centre In total, 386 people qualified and their medical records were analysed for the study.The study was conducted using three popular cognitive ability screening tests, which were translated into Polish: MMSE—a most often applied 30-point test with international and interdisciplinary recognition; ACE-III—a developed 100-point test, which allows early differential diagnosis; M-ACE—a shortened 30-point version of ACE-III, feasibly administered within a time frame comparable to MMSE.MMSE was first published in 1975 . It was ACE-III is an international test used for both overall assessment and selective assessment within five cognitive domains. It is considered a targeted tool meant as a screening assessment of particular dysfunctions or, in other words, used for screening differential diagnoses . The curAttention: score 0–18,Memory: score 0–26,Verbal Fluency: score 0–14,Language: score 0–26,Visuospatial Abilities: score 0–16.ACE-III is a test that assesses the following five cognitive domains: attention, memory, verbal fluency, language and visuospatial abilities, with scores within the following ranges:The test’s structure allows an assessment of particular cognitive domains, as it addresses specific difficulties and deficits.M-ACE is a shorter version of ACE-III. It is often referred to as mini-ACE or MACE. The test was developed at Neuroscience Research Australia. It is available in various language versions and multiple adaptations, including a Polish version ,9,22.A partly structured interview was conducted, comprising the educational and professional background, selected aspects of social functioning, health and conditions, which could impact cognitive functions, such as hypothyroidism, cardiovascular diseases, mental disorders and others. Participants with the following conditions were excluded from the study: sense organ disorders (unless participants had the recommended prescriptive glasses or a hearing aid), intractable non-nociceptive pain, suspected but untreated cases of severe depression, psychiatric disorders severe enough to prevent assessment. Participants who displayed any of the symptoms above were referred to a specialist for diagnosis and treatment. People over 60 years of age, capable of linguistic, visual and auditory communication in a stable somatic state, were included in the study. Persons declaring severe somatic complaints or pain, as well as those whose mental state required medical intervention in the first place, were excluded.MMSE and ACE-III screening tests were conducted, and the results were used to calculate the M-ACE results.In accordance with the standards of psychological assessment, each participant was presented with the results of the assessment and further recommendations.The assessment procedure was conducted identically for each participant:The results were given as a standard deviation, mean and median; the results were checked for normal distribution. If the results failed to meet normal distribution, the variables were analysed by using nonparametric tests.The groups were analysed for such characteristics as age, sex and years of schooling. Next, the raw data from each screening test were analysed.raw MMSE results and age, sex or years of schooling;ACE-III results and age, sex or years of schooling;results of M-ACE and age, sex or years of schooling.Step one of the analysis included 386 people. Personal characteristics were given based on the means, the median and allowing for standard deviation for each variable: age or years of schooling. Next, an effort was made to establish the following relations in the groups under study:r = 0—no correlation,r < 0.2—remote correlation,0 < r < 0.4—weak correlation,0.2 ≤ r < 0.6—average (medium) correlation,0.4 ≤ r < 0.8—high (strong) correlation,0.6 ≤ r < 1—very high (very strong) correlation,0.8 ≤ r = 1—perfect correlation (complete).Step two of the analysis comprised the Spearman’s rank correlation coefficient to compare the sensitivity of each screening test with regard to the assessment of cognitive function in differentiating norms and results below the norm. The following criteria were adopted:MMSE and ACE-III,MMSE and M-ACE,ACE-III and M-ACE.The analytics were conducted for:Further calculations performed using McNemar’s test were meant to determine the rate of patient migrations between the ranges of the norm and the below the norm results  for each test in comparison with MMSE. Data that showed significant changes in patient migration between the two categories allowed us to differentiate between patients with disorders and healthy participants, assuming a possibly low number of erroneous classifications. Thus, the true positive, true negative, false negative and false positive values were established. Further analysis made use of the ROC curve with the aim to assess the test’s ability to differentiate between the objects with and without a particular feature. For each test, the ROC characteristics were established based on the result category obtained, so as to set the cut-off points of highest sensitivity and specificity. For the purpose of this study, the optimum cut-off point on the ROC curve was developed based on the cost of wrong decisions. The cost of wrong decisions was computed under the assumption that all errors are equally costly.During the next stage, the analysis aimed to draw comparisons between the tests for the three categories: norm, MCI and dementia. The comparison was conducted to verify whether there occurred a statistically significant discrepancy in cross-category patient migration within the three categories for either scale. Prior calculations were grouped into categories, which differentiated between normal, slightly lower results (which could point to mild cognitive disorders constituting a risk factor for developing dementia) and dementia. Bowker’s test of internal symmetry  was used here to verify the hypothesis determining the symmetry of two results of measurements executed twice and a feature, which might have more than two categories .To establish those areas of cognitive functioning whose lower performance occurs first and, thus, could be an early predictor of the disease, the results of the targeted ACE-III test were compared with the MMSE results for the norm range. As ACE-III consists of several domains, a low score in any of the domains lowers the overall result. The analysis of ACE-III revealed which domains might influence the final outcome more, with patients scoring below the norm threshold in ACE-III, despite being classified as within the norm range by MMSE.The results were computed using the Mann–Whitney U-test, used to verify a hypothesis determining the insignificance of differences between the medians of the analysed variables, assuming the two distributions of the variables to be quite alike . This helped ascertain the data for the particular cognitive domain sub-tests, which scored lower than the norm threshold in ACE-III in patients whose results were within the norm on the MMSE scale.Step one of the analysis pertained to the discrepancies among the mean scores for the domains of Attention, Speech Fluency, Memory, Language and Visuospatial Ability in people who scored within norm results obtained in MMSE and within norm and below norm results in ACE-III. However, as each domain in ACE-III is characterised by a different scale range, the percentage values were used next. Thus, each scale was assigned a range of 0–100% according to the formulap < 0.001).In total, 386 people took part in the study, including 302 women (78.2%) and 84 men (21.8%). The mean age was 76.9 ± 8.3 years . Women were younger than men to a statistically significant degree  vs. M: 79.5 ± 7.8 years ; On average, participants declared 13.4 ± 3.2 years of schooling . The mean length of schooling was comparable for either sex  vs. M: 13.5 ± 3.4 years ).MMSE was conducted for all 386 study participants. On average, the overall result was 25.7 ± 4.3 , with 217 people, that is, 56.2% of participants, scoring in accordance with their age norm. Seventy-nine people, that is, 20.5% of participants, scored below the cut-off point of 26 pts but above 23 pts, a range characteristic of high risk of dementia and—in the case of MMSE—a range assumingly corresponding to mild cognitive disorders. The number of people who scored below 24 pts, that is, below the cut-off point, was 90, constituting 23.3% of all participants. This group is very likely to have dementia.r = −0.494; p = 0.0000). The correlation was negative—the older the respondent, the lower the result in MMSE.There was a statistically significant correlation between the age of participants and their score results for MMSE (p < 0.0001). The mean scores for MMSE depending on the age group profile are presented in Additionally, there occurred a statistically significant difference in MMSE results in patients of varying ages . The older the participant, the lower they scored in MMSE . The correlation was positive—the more years of schooling, the better the score in MMSE  was 78.5 ± 16.8 .Attention (pts)—15.5 ± 2.9 , range 0–18 pts;Fluency (pts)—9.0 ± 3.5 , range 0–14 pts;Memory (pts)—18.1 ± 6.9 , range 0–26 pts;Language (pts)—22.7 ± 4.0 , range 0–26 pts;Visuospatial Abilities (pts)—13.2 ± 2.6 , range 0–16 pts.For each component corresponding to a particular domain, the average score was:Among the group tested by means of ACE-III, assuming cut-off points of 88 and 82 points, 150 people, which is 38.9% of the participants, scored within the norm, while 62 people, that is, 16.1%, obtained between 88 and 82 points, which effectively puts them in the range associated with a higher risk of dementia. In clinical terms, this range is characterised by selective or general deficits in cognitive functioning typical for MCI. Lastly, 174 people, which comprises 45.1% of the test group, obtained scores indicating a high likelihood of dementia.r = −0,5887; p = 0.0000). The older the participants, the lower the ACE-III test results . The higher the number of years of schooling, the higher the score obtained in ACE-III .Based on the M-ACE test results, assuming cut-off points of 25 and 21 points, as suggested by the test authors considering the validation carried out for the toolkit, 138 people (35.8% of the participants) scored within the norm; 92 people, which amounts to 23.8%, obtained results, which could point to a higher risk of dementia; and 156 people, which is 40.4% of the test group, scored within a range characteristic of a high likelihood of dementia.r = −0.56914; p = 0.0000) and a positive correlation between years of schooling and M-ACE test results . The older the participant, the lower they scored in M-ACE. However, the higher the number of years of schooling, the higher the score obtained in M-ACE. Detailed characteristics can be seen in The research showed a statistically significant negative correlation between age and M-ACE test results  was carried out to compare the sensitivity of the tests to MMSE raw data. Statistically significant positive correlations were found for the scales:n = 77; 35.5%) scored below the norm in ACE-III (0–88 pts). Among 150 (38.9%) respondents whose scores ranged within the norm in ACE-III (89–100 pts), only 10 people (6.7%) scored below the norm in MMSE (0–26 pts).Among 217 (56.2%) participants who scored within the norm in MMSE (27–30 pts), every third participant  people whose test results placed them in the same category (below the norm or norm) on both scales. They accounted for 77.5% (41.2 + 36.3%) of all participants. Ten participants (2.6%) whose MMSE test results placed them within the below-norm category scored within the norm in ACE-III. Meanwhile, 77 people (19.9%) whose MMSE scores categorised them within the norm obtained below-norm scores in ACE-III.2 = 50.1; p < 0.0001). As compared to MMSE, more people (77) crossed over to a lower category than to a higher category (10 people).McNemar’s test revealed a statistically significant change in patient cross-category migration between MMSE and ACE-III .For ACE-III, the suggested cut-off point was 81. For this cut-off point, the costs of erroneous decisions were at a minimum . At the cut-off point of 81, the values of sensitivity and specificity reached their peak value  .n = 242) obtained scores that placed them within the same category  in both ACE-III and MMSE. For 12 respondents (3.1%), the ACE-III category was increased as compared with MMSE.Considering how significant, in clinical terms, the difference between the category of MCI and the category of dementia is, particularly since it concerns prognosis and the recommended course of treatment, an additional analysis including MCI as a separate category was conducted. Among the study participants, only 62.7% (Two people (0.5%) whose MMSE results allocated them to the category of dementia received the status of MCI in ACE-III.Ten people (2.6%) whose scores assigned them to the category of MCI in MMSE were classified within the norm in ACE-III.For 132 respondents (34.1%), the category obtained in ACE-III was lower as compared with MMSE.Fifty-five people (14.2%) who were categorised as MCI in MMSE obtained results classified as dementia in ACE-III.Thirty-one people (8.0%) whose scores classified them as within the norm in MMSE obtained results classified as dementia in ACE-III.Forty-six people (11.9%) whose scores allocated them within the norm in MMSE obtained the status of MCI in ACE-III.2 = 98.3; p < 0.0001); more people crossed over to a lower category (132 people) than to a higher category (12 people) in ACE-III as compared with MMSE.There occurred a statistically significant difference in patient cross-category migration between MMSE and ACE-III classifications . Within this group, there were statistically significant differences observed between people who scored below the norm (0–88 pts) and those within the norm (89–100 pts) for either of the five domains of ACE-III. People whose test results fell within the norm in ACE-II scored higher in the domains of Attention, Verbal Fluency, Memory, Language and Visuospatial Abilities. The next stage of the analysis comprised a search for more subtle functioning differences in people whose test results were within the norm in either test and people who scored within the norm in MMSE and below the norm in ACE-III. Thus, people with the measurement executed once and whose MMSE test results ranged between 27 and 30 points were also included in this part of the study . Indirectly, the difference between the people within the norm and below the norm could be derived from the Z value of the Mann–Whitney U-test results . A detailed description is shown in Thus, allowing for the differences in mean scores, the domain of Memory presented the highest difference. However, as each domain in ACE-III is characterised by a different scale range, the percentage values were used next. Thus, each scale was assigned a range of 0–100% according to Formula (1) in Attention 1 pt = 5.6%,Fluency 1 pt = 7.1%,Memory/Language 1 pt = 3.8%,Visuospatial Abilities 1 pt = 6.3%.This yielded the following results:For Fluency, the difference in the mean score was 0.7 points, corresponding to the difference in percentage means of 3.9%. Analogically, for the other domains, the differences in the percentage mean were as follows: Fluency—26.4%; Memory—20.4%; Language—9.2%; and Visuospatial Abilities—11.3%.The domains of Fluency and Memory had the greatest influence on cross-categorising MMSE within the norm scores to scores below the norm in ACE-III. A detailed profile can be found in Out of 217 (56.2%) participants who scored within the norm in MMSE (27–30 pts), 90 respondents (41.5%) obtained a score below the norm in M-ACE (0–25 pts). Among 138 (35.8%) respondents who scored within the norm in M-ACE (26–30 pts), only 11 people (8.0%) were classified below the norm in MMSE (0–26 pts).n = 285) of study participants obtained scores, which placed them within the same category in both M-ACE and MMSE. One hundred and eleven respondents (2.8%) whose scores categorised them as below the norm in MMSE received the category of within the norm in M-ACE. Meanwhile, 90 people (23.3%) whose MMSE test results placed them within the norm obtained below-norm results in M-ACE.A total of 73.8% ; more people were categorised as lower category (90 people) than higher category (113 people) in M-ACE as compared to MMSE.McNemar’s test revealed a statistically significant change in patient cross-category migration between MMSE and M-ACE .For M-ACE, the suggested cut-off point was 20. For this cut-off point, the costs of erroneous decisions were minimal . With a cut-off point of 20, the value for sensitivity was 0.769, while for specificity, it was 0.880; however, neither value reached its peak at this cut-off point. Sensitivity and specificity simultaneously reached their maximum values at the cut-off point of 21  .n = 242) obtained scores that placed them within the same category  in both ACE-III and MMSE. For 14 people (3.7%), the category obtained in M-ACE was higher than the category allocated in MMSE:Three people (0.8%) who were assigned to the category of dementia in MMSE received the category of MCI in M-ACE;One person (0.3%) whom the MMSE test results placed in the category of dementia obtained the status of MCI in M-ACE;Ten people (2.6%) whose scores categorised them as MCI in MMSE were allocated within the norm in M-ACE.Among the study participants, only 62.7%  had their category lowered in M-ACE as compared to MMSE:Forty-four people (11.4%) who were assigned MCI in MMSE obtained the category of dementia in M-ACE;Twenty-six people (6.7%) whose scores allocated them to within the norm in MMSE were classified as dementia in M-ACE;Sixty-four people (16.6%) who scored within the norm in MMSE received the status of MCI in M-ACE.Every third person ; more people were assigned to a lower category (134 people) than a higher category (14 people) in M-ACE as compared to MMSE.The Bowker–McNemar test showed that there occurred a statistically significant change in patient cross-category migration between the MMSE and M-ACE tests , what also impacts the situation are cultural factors, such as unwillingness to seek professional help in mental disorders, which is connected with a fear of stigma, more often than not observed in older people, and especially men . The othisorders . For insisorders .The study revealed that the test results declined with age; however, it was people under 70 who obtained the highest scores. Additionally, people between 71 and 80 years of age displayed significantly higher test results than people over 80, which supports the claim that problems in engaging the cognitive processes in test-solving tasks increase with age but also result from health conditions in people who apply for help at geriatric health care centres. This line of reasoning finds support in the latest research on the cognitive functioning of the oldest—those over 80 years old ,28,29.Education is a crucial factor that impacts cognitive agility in older people. It constitutes an element of the cognitive reserve (CR), which is a cognitive strategy and skill set that allow us to compensate for shortcomings, which stem from neurodegeneration ,30,31. TFor each assessment with the use of ACE-III and M-ACE, the distribution was calculated based on the score range of the norm, the range below the norm corresponding to MCI and the below-norm range suggestive of dementia. Additionally, the raw data from all three diagnostic tools were correlated, which helped establish high and very high correlations between MMSE and ACE-III . Consequently, the test results for all three methods are coherent.Further analysis confirmed that the area under the ROC curve for the ACE-III diagnostic variable had a high value (AUC = 0.920), and a new cut-off point of 81 points was suggested to differentiate between healthy and ill people. The new threshold was lower than the original cut-off point by 1 point, with respect to the bottom cut-off point, and by 7 points, with respect to the top cut-off point. The latest research on Chinese versions of the test suggests a cut-off point of 85, with AUC = 0.978 ; meanwhiCompared to M-ACE, the area under the ROC curve was also very high (AUC = 0.891), and the suggested cut-off point was 20 points, and it was lower by 1 point, with respect to the original bottom threshold, and by 5 points, with respect to the top cut-off point. Meanwhile, compared to Larner’s suggestions, the cut-off point proposed here was 4 points lower, with respect to the top cut-off point, but equal to the bottom cut-off point . FollowiThus, further analysis was performed based on calculations, which included an additional category: MCI. Research showed that nearly 62% of participants obtained a score within the same category across all three screening tests: ACE-III, M-ACE and MMSE . In ACE-III, merely 3.1% of participants were moved a category higher, from dementia to MCI or from MCI to within norm, as compared to the MMSE test results. As many as 34.1% of participants had their category lowered in ACE-III as compared to MMSE, with 14.2% crossing from MCI to dementia, 8% having the category shifted from within norm to dementia, and 11.9% being recategorised from within norm to MCI. Similarly, in M-ACE, 34.7% had their category lowered, including as many as 16.6% being shifted from within the norm to MCI. This testifies to the high sensitivity of each test to differentiate between healthy people and those living with a disorder, with ACE-III (to a greater degree) and M-ACE being capable of more detailed ability to differentiate between MCI and healthy population or MCI and dementia. Similar results were reported in analogical research abroad , while vFurther analysis in this study aimed to identify those ACE-III sub-tests whose results deviated from the norm to a large extent as compared to results within the norm obtained with MMSE. The most dramatic decrease in the mean score values for people who scored below or within the norm of the ACE-III test, as compared to the MMSE norm, occurred for speech fluency (decrease of 26.4%), followed by memory (decrease of 20.4%), visuospatial functioning (decrease of 11.3%), language function (decrease of 9.2%). Attention mean values decreased the least, by only 3.9%. This points to a crucial significance of the task, which forces respondents to search their mental schemata mediated by lexical means under time pressure , in identifying the earliest predictors of cognitive deficits. The other telling domain is the mnestic one, which MMSE is hardly equipped to verify. Deficits in either of those cognitive domains, memory or fluency, are essential in dementia onset and development, including the most frequent forms of dementia. These include amnestic AD ,37, whicThe results of this study indicate that common knowledge on the characteristics of particular screening tests and their diagnostic applications must be verified. M-ACE seems most advantageous compared to MMSE when it comes to a rapid screening assessment of cognitive functioning. Moreover, adjusted MMSE scoring for education, although useful in clinical practice, as it mitigates the risk of a false positive diagnosis, requires additional information about the patient and professional experience. Targeted ACE-III seems best recommended for use in specialised diagnostic centres as a screening tool , whereas


A pre-test/intervention/post-test/9-month-follow-up design was used. Outcome measures included assessments of language  and working memory . Hierarchical multiple regression analyses controlling for pre-intervention performance and age found the group to be a significant predictor of sentence comprehension and of performance on six untrained working-memory measures at post-intervention and 9-month follow-up. Children in the intervention group showed significantly higher language comprehension and working-memory scores at both time points than children in the active control group. The intervention programme showed the potential to improve working memory and language comprehension in children with DLD and demonstrated several advantages: it involved short sessions over a short period, caused little disruption in the school day, and was enjoyed by children.Recent research has suggested that working-memory training interventions may benefit children with developmental language disorder (DLD). The current study investigated a short and engaging adaptive working-memory intervention that targeted executive skills and aimed to improve both language comprehension and working-memory abilities in children with DLD. Forty-seven 6- to 10-year-old children with DLD were randomly allocated to an executive working-memory training intervention ( The current investigation concerns a short and engaging adaptive working-memory training intervention that aimed to improve both language comprehension and working memory in children with developmental language disorder. As well as looking at ‘far transfer’ to two measures of language comprehension (sentence comprehension and receptive grammar), the study included six measures of ‘near transfer’ to assess whether the intervention led to gains in working-memory tasks that were not directly trained.The working-memory system is widely accepted as describing the way information is processed and retained  and can Researchers have emphasised that understanding working-memory development is crucial for helping children maximize their intellectual progress . There aThese associations between working memory and other cognitive processes, as well as the lower working-memory performance of children with developmental conditions, underpin the interest in using interventions to improve working memory and related neuropsychological abilities. An investigation of a computerised working-memory intervention targeting the central executive found that, following training, performance on components of the working-memory system improved, and importantly, non-verbal intelligence also improved . These eHowever, systematic reviews to date have usually been concerned with computer-based interventions that attempt to improve at least one component of the working-memory system ,24,25,26It remains important to understand how working-memory interventions might benefit children with developmental conditions. Rowe et al.  emphasisSeveral recent investigations of working-memory interventions have concerned children with developmental language disorder (DLD) or a related diagnosis. DLD is a persistent neurodevelopmental condition, involving a primary difficulty with language that is unexplained by any other syndrome or circumstances ,32. DLD Newly emerging evidence suggests a more promising role for working-memory interventions in children with DLD. For example, in a study using a pre-test/intervention/post-test design, Holmes et al.  used theAcosta-Rodríguez, Ramírez-Santana, and Hernández-Expósito  used a cIn two other investigations, far-transfer effects of working-memory training have been reported on syntax with French children who have DLD ,39. StanThe present investigation of the effectiveness of an executive working-memory training intervention for children with DLD builds on these findings. We focussed on children with DLD because of the suggestion that children with developmental conditions may be more likely to benefit from working-memory interventions, as there is more room for improvement. Children with DLD are known to have difficulties with working memory, which encompass both short-term and executive working memory ,43,44,45The current intervention followed a programme used by Henry et al. , who repThe overall research question was: For children with DLD, are there immediate and longer-term effects of EWM training? We assessed immediate and longer-term effects for directly trained EWM tasks, working-memory tasks that were not trained (near transfer) and language comprehension (far transfer).Fifty-one participants aged six to ten years with language difficulty as a primary need were recruited from six mainstream primary schools  across Dorset and Hampshire (UK). Study inclusion criteria were: age 6–11 years, language difficulty identified as a primary need (and two or more language scores at or below one standard deviation of the mean on screening), nonverbal IQ of 70 or above, no formal diagnosis of autism, and English as a first spoken language at home.The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the relevant university Ethics Committee. Written informed consent was sought and obtained from all parents/guardians of participating children, and verbal assent was obtained from the children themselves. Schools recommended suitable children, and following the consent process, screening tasks were undertaken. These included: the four core subtests from Clinical Evaluation of Language Fundamentals 4 (CELF-4-UK) , the Wecn = 24) or an active control group (n = 23). Excluding the researcher, all other individuals including staff at the schools were blind to this random allocation. The researcher was aware of the participant’s group membership as practical limitations made it impossible to conduct a double-blind experiment. Screening scores for both groups are given in t-tests for group differences . No significant group differences on the screening variables were found, although there was a tendency for the active controls to show numerically lower language scores.Children who fulfilled the study inclusion criteria were randomly assigned by an independent colleague to one of two groups, a working-memory training intervention group , and the child completes an orally presented sentence related to an illustration, e.g., ‘Here is one book. Here are two _____’. There was no discontinuation point and all children were administered 32 sentences. Recalling Sentences evaluates a child’s ability to recall and produce sentences varying in length and syntactic complexity. Orally presented sentences are repeated back by the child and scored for errors. Full recall with no errors gains a score of three, one error a score of two, two to three errors a score of one and more than four errors a score of zero. After five consecutive scores of zero, the subtest was discontinued. Formulated Sentences required the child to formulate semantically and grammatically correct sentences using a target word to describe a given picture. Depending on the grammatical and semantic correctness of a sentence, a child was given a score between zero and two for each item. If a child obtained five consecutive scores of zero, the subtest was discontinued.The WASI–II  assessedAll children were administered outcome assessments before the working-memory intervention commenced, immediately after 18 intervention sessions were completed and at a 9-month follow-up. Outcome measures related to direct training effects (the two trained executive working-memory tasks), far-transfer effects (measures of sentence comprehension and receptive grammar), and near-transfer effects (short-term and executive working-memory tasks that were not trained). Raw scores are reported for all outcome measures as standardised tests were not available for some tasks , and age was controlled in all relevant analyses. See Listening recall from the Working-Memory Test Battery (WMTB-C)  was admiThe Odd One Out Span task  assessedThe Sentence Comprehension subtest from the Assessment of Comprehension and Expression (ACE)  was admiThe Test for Receptive Grammar Version 2 (TROG-2)  measuresFour tasks assessed short-term working-memory abilities . For five of the measures , the taDigit Recall (WMTB-C) assessed verbal short-term memory and involved the experimenter reading out a list of numbers which the child repeated back in the correct order. The test–retest reliability for Digit Recall ranges from 0.81 to 0.82.Word List Recall (WMTB-C) assessed verbal short-term memory and involved the experimenter reading out a list of one syllable words which the child repeated back in the correct order. The test–retest reliability for Word List Recall ranges from 0.64 to 0.80.Block Recall (WMTB-C) assessed spatial short-term memory and involved showing the child a board with nine randomly spread out identical raised cubes . The researcher tapped a series of one or more spatial positions on the blocks and asked the child to recall the positions by tapping the same sequence immediately afterwards. The test–retest reliability for Block Recall ranges from 0.43 to 0.63.Counting Recall (WMTB-C) assessed executive working memory and required the child to count, out loud, the number of dots that were presented to them in a stimulus book. After counting the dots, the researcher turned the page of the stimulus book, and the child was asked to recall the number of dots they previously counted. Trials started with a single page of dots and were given in list lengths of six, as per the other tests. The test–retest reliability for Counting Recall ranges from 0.48 to 0.74.Backward Digit Recall (WMTB-C) assessed executive working memory and involved the experimenter reading out a list of numbers, which the child had to repeat backwards. The test–retest reliability for Backward Digit Recall ranges from 0.53 to 0.71.r = 0.71 between trial 1 and trial 2 scores, r = 0.79 between trial 1 and trial 3 scores, and r = 0.82 between trial 2 and trial 3 scores).A measure of the Pattern Span was developed, based on that of Della Sala et al. , to asseFor the screening phase, the researcher visited the child at school and administered the CELF-4-UK subtests and the WASI-II Perceptual Reasoning Index tasks. Following random allocation to working-memory training and active control groups, children completed assessments in working memory (eight tasks), sentence comprehension and receptive grammar . Next, children received the working-memory training intervention (see below) and, following the intervention, all outcome measures were administered again. After a delay of around 9 months, outcome measures were administered once more to assess maintenance.Those assigned into the working-memory training group undertook the full intervention protocol over a six-week period. During the intervention, all children were visited three times a week within their school setting at the same time each week, in a quiet area either in a separate classroom, library area or intervention room. Each child spent around 10 min with the researcher administering 11 trials similar to those in the Listening Recall task  and 11 tThis training task  focusedThe listening recall training materials comprised six sets of sentence stimuli for every list length between one and seven, which could be drawn from during the training session to produce trials at the appropriate level. The first training trial began at the child’s span level, established from pre-intervention testing. If the span level was previously zero, the researcher started at span level one. The researcher orally presented the requisite number of sentences depending on the start span level, each was judged as true or false by the child, and the child attempted to recall the final word from each sentence. Two trials at the initial span level were presented. If both trials were answered correctly, the researcher moved the child up one span level, increasing the task difficulty. If both trials were answered incorrectly, the researcher lowered the span level by one . If the child answered one trial correctly and one trial incorrectly, the span level remained the same for a further two trials. The training continued in this format until the child answered 11 trials. At the end of the 11 trials, the researcher calculated the most commonly administered span level and recorded this on the record form so that this would be the start level for the next training session. The process was repeated for the next 17 training sessions of the working-memory intervention.The children assigned to the active control group were also administered 11 trials per session but were not required to recall the final word of the sentence. Thus, the active control group just needed to identify whether the sentence was true or false, removing any working-memory requirement to the task.This training task (adapted from Odd One Out Span ) focusedAs for the Listening Recall training task, the first training trial began at the child’s span level, established from pre-testing, unless the span level was previously zero, in which case, the researcher started at span level one. Again, the working-memory training was designed to be adaptive, so it increased in difficulty if the child’s memory span performance increased, stayed at the same difficulty if the level was exactly at the child’s level, or decreased in difficulty if span had been exceeded. At the end of the 11 training trials, the most frequently presented list length was carried over to the next session as the ‘starting point’. The process was repeated for the next 17 training sessions of the working-memory intervention.Children who had been assigned to the active control group were also administered 11 ‘Odd One Out’ trials but made the ‘odd-one-out’ judgment only, i.e., they were not required to recall the spatial locations. For the active control, therefore, the same materials were used, and the same interaction was included with the researcher as for the intervention, removing any working-memory requirement to the task.Mean raw scores for pre-intervention, post-intervention and 9-month follow-up on all outcome measures are given in t(45) = −0.23, p = 0.819 ;Listening Recall, t(45) = 0.28, p = 0.782 ;Odd One Out, t(45) = 1.17, p = 0.25 ;Sentence Comprehension, t(45) = 1.62, p = 0.113 ;Receptive Grammar, t(45) = 0.82, p = 0.415 ;Digit Recall, t(45) = 1.90, p = 0.064 ;Word List Recall, t(45) = 0.37, p = 0.711 ;Block Recall, t(45) = 0.74, p = 0.465 ;Pattern Span, t(45) = 0.80, p = 0.427 ;Counting Recall, t(45) = 0.87, p = 0.389 .Backwards Digit Recall, There were no significant differences between groups on any pre-test scores  was a significant predictor of post-intervention and 9-month follow-up outcome scores. In all regressions, pre-intervention scores for the relevant outcome measures and age in months were controlled at step one. Controlling for pre-intervention outcome scores was a conservative approach as it ensured that any initial variations in performance across participants and groups were taken into account . Age wasFor all regression analyses, key statistical checks were carried out . In some regression analyses, one child in the working-memory training group improved on an outcome measure more than the model predicted, resulting in a high standardised residual (outlier). When this occurred, regressions were re-run after removing the relevant case, but as there were never any substantive differences in findings, original analyses are reported.p < 0.01). See The first analyses assessed whether training intervention effects were present on the two trained executive working-memory tasks. As four separate regression analyses were conducted (two directly trained executive working-memory tasks at two time points), Bonferroni corrections were made to the significance levels for the overall models (R2 (∆R2); here, group accounted for a further 33.8% of the variance. The final model was significant, F = 51.06, p < 0.001, predicting 78.1% of the total variance (Adj. R2 0.766). At 9-month follow-up, pre-intervention scores and age accounted for 44.9% of the variance at step one, with only pre-intervention score as a significant individual predictor. Adding group at step two again produced a significant change in R2 (∆R2), with group accounting for a further 35.8% of the variance. The final model was significant, F = 59.89, p < 0.001, predicting 80.7% of the total variance (Adj. R2 0.793).For post-intervention Listening Recall, at step one of the regression, the pre-intervention scores and age accounted for 44.3% of the variance. Examination of the standardised beta-values indicated that only the pre-intervention score was a significant individual predictor; this was not unexpected as pre-intervention scores are an important predictor for scores after intervention. In step two, adding group produced a significant change in f2 = 0.51) at post-intervention and 6.85 points lower (f2 = 0.56) at 9-month follow-up. Note: for Cohen’s f2 [f2 = 0.02 small; f2 = 0.15 medium; f2 = 0.35 large.The training group differences on Listening Recall were large, even after controlling for pre-intervention score and age. Inspection of unstandardised beta values (B) in hen’s f2 , the effR2 (∆R2), accounting for a further 48.3% of the variance; here, age became a significant predictor alongside pre-intervention score and group. The final model was significant, F = 51.58, p < 0.001, predicting 78.3% of the total variance (Adj. R2 0.767). At 9-month follow-up, pre-intervention scores and age accounted for 31% of the variance, with pre-intervention score a significant individual predictor. Adding group at step two produced a significant change in R2 (∆R2), accounting for a further 47.2% of the variance; here, age again became a significant predictor alongside pre-intervention score and group. The final model was significant, F = 51.47, p < 0.001, predicting 78.2% of the total variance (Adj. R2 0.767).For post-intervention Odd One Out, at step one, the pre-intervention scores and age accounted for 30% of the variance, with the pre-intervention score representing a significant individual predictor. Adding group at step two produced a significant change in f2 = 0.93) at post-intervention and 9.04 points lower (f2 = 0.90) at 9-month follow-up.The training group differences for Odd One Out were very large, even after controlling for pre-intervention score and age. Inspection of unstandardised beta values in The working-memory intervention led to substantial and significant gains in performance for those in the working-memory training group on two directly trained tasks, Listening Recall and Odd One Out span, with very large effect sizes. These findings were present at both time points and were found even after controlling for pre-intervention performance and age.p < 0.01). See We next assessed whether there were far-transfer effects to Sentence Comprehension and Receptive Grammar skills, either immediately post-intervention or at 9-month follow-up. As four separate regression analyses were conducted , Bonferroni corrections were made to the significance levels for the overall models (R2 (∆R2), accounting for a further 10.4% of the variance. The final model was significant, F = 53.61, p < 0.001, predicting 78.9% of the total variance (Adj. R2 0.774). At 9-month follow-up, pre-intervention scores and age again accounted for a substantial 66.2% of the variance at step one, with only pre-intervention score a significant individual predictor. Again, in step two, adding group produced a significant change in R2 (∆R2), accounting for a further 9.7% of the variance. The final model was significant, F = 45.08, p < 0.001, predicting 75.9% of the total variance (Adj. R2 0.742).For post-intervention Sentence Comprehension, at step one, pre-intervention scores and age accounted for a substantial 68.5% of the variance, with only pre-intervention score a significant individual predictor. Of particular interest was the effect of adding group in step two, which produced a significant change in f2 = 0.12) at post-intervention and 3.60 points lower (f2 = 0.11) at 9-month follow-up. The gains after training approached a medium effect size. If we consider the average pre-intervention Sentence Comprehension score in our working-memory training group (raw score = 21), together with their average age (8 years 0 months), a raw score of this value gives a scaled score of 6 according to the manual [Thus, even with our conservative approach of controlling for the substantial variance accounted for by pre-intervention scores and age, training group was a significant predictor of Sentence Comprehension both immediately and nine months following the intervention. Inspection of unstandardised beta values in e manual . An incrR2 (∆R2), accounting for only a further 2.5% of the variance. The final model was significant, F =18.59, p < 0.001, predicting 56.5% of the total variance (Adj. R2 0.534). At 9-month follow-up, pre-intervention scores and age accounted for 58.1% of the variance at step one, with pre-intervention score a significant individual predictor. In step two, adding group, failed to produce a significant overall change in R2 (∆R2), accounting for a further 3.5% of the variance. The final model was significant, F = 22.93, p < 0.001, predicting 61.5% of the total variance (Adj. R2 0.589).For post-intervention Receptive Grammar, pre-intervention scores and age accounted for 54% of the variance in post-intervention scores at step one, with pre-intervention score a significant individual predictor. In step two, adding group did not produce a significant change in f2 = 0.03) at post-intervention and 1.50 points lower (f2 = 0.04) at 9-month follow-up (neither group difference was significant). In the latter case, however, there was a marginally significant effect of group (p < 0.055) with a small effect size.The training group was not a significant predictor of Receptive Grammar at post-intervention or 9-month follow-up, although children in the working-memory training group did obtain numerically higher scores. Inspection of unstandardised beta values in The working-memory intervention led to significant gains for those in the working-memory training group on Sentence Comprehension (three to four points in the raw score), which approached a medium effect size. These findings were evident both immediately post-intervention and at 9-month follow-up and were found even after controlling for pre-intervention performance and age. No significant training group differences were found for Receptive Grammar.p < 0.004). See Also of interest was the possibility of near-transfer effects to related working-memory tasks that were not directly trained, both immediately after the intervention and at 9-month follow-up. We assessed four short-term working-memory measures  and two executive working-memory measures . As 12 separate regression analyses were conducted , Bonferroni corrections were made to the significance level for the overall models  ranged between 20.24 and 54.00, all ps < 0.001). Pre-intervention scores and age accounted for between 40.6% and 67.4% of the variance at step one in all eight models, and only pre-intervention scores were significant individual predictors in each case. At step two, adding group produced a significant change in R2 (∆R2) in all eight models, accounting for additional variance of between 10.8% and 24.0%. Being in the working-memory training group was associated with significantly higher scores on all four short-term memory assessments at both time points. The total variance accounted for in the models ranged from 58.5% to 79.0%.For the four short-term working-memory measures, all regression models at post-intervention and 9-month follow-up were significant  and between 3.90 and 6.29 points lower at 9-month follow-up .Group differences associated with being in the working-memory training group were medium to medium-large across all near-transfer short-term memory measures, even after controlling for pre-intervention scores and age. Inspection of unstandardised beta values in Fs between 36.87 and 56.15, all ps < 0.001). Pre-intervention scores and age accounted for between 62.2% and 71.0% of the variance at step one, and only pre-intervention scores were significant individual predictors in each case. At step two, adding group produced a significant change in R2 (∆R2) in all models, accounting for additional variance of between 7.5% and 12.9%. For both EWM tasks at both time points, being in the trained group was associated with significantly higher scores. The total variance accounted for in these models ranged from 72.0% to 79.6%.For the two untrained executive working-memory measures, all regression models at post-intervention and 9-month follow-up were significant ; and 5.34 and 3.17 points lower at 9-month follow-up .Group differences associated with being in the working-memory training group were medium to medium-small for the near-transfer executive working-memory measures, even after controlling for pre-intervention scores and age. Inspection of unstandardised beta values in The working-memory intervention led to significant gains for those in the working-memory training group on all six untrained working-memory tasks, encompassing both short-term and executive working memory, usually with medium effect sizes. This provided strong evidence for near transfer to similar working-memory tasks. These findings were evident both immediately post-intervention and at 9-month follow-up and were found even after controlling for pre-intervention performance and age.This study investigated whether an adaptive intervention targeting executive working memory would benefit children with developmental language disorder, as evidenced by improvements not only on the two trained tasks (direct effects) and six untrained working-memory tasks (near-transfer effects), but also on tests of Sentence Comprehension and Receptive Grammar (far-transfer effects). Outcomes were measured immediately post-intervention and nine months later. To specifically evaluate the contribution of an executive working-memory training intervention, the study randomly assigned participants to a ‘trained’ group who received the executive verbal and visuospatial tasks  and an ‘active control’ group who received the same tasks but without the executive element. Hierarchical multiple regression analyses controlling for pre-intervention performance and age found group to be a significant predictor of Sentence Comprehension at both time points. These findings indicated that children in the working-memory training group obtained significantly higher scores on Sentence Comprehension than children in the active control group immediately following training, and that these gains were maintained nine months later. We estimated how the intervention affected the children’s percentile scores on Sentence Comprehension. Calculations suggested that the intervention could result in a change from the 9th to 37th percentile, an appreciable gain, as after the intervention scores would reach the low-typical range. Performance on Receptive Grammar, however, did not show these gains, with only a marginal group effect at 9-month follow-up.In terms of direct and near-transfer effects, group was a significant predictor of performance on both the trained executive working-memory tasks  and performance on all other near-transfer working-memory tasks  immediately post-intervention and nine months later. For all tasks, children in the working-memory training group obtained significantly higher scores than children in the active control group at both time points, even after controlling for pre-intervention performance and age.The findings of positive near and far-transfer effects of the working-memory training in this study run counter to earlier systematic reviews that have concluded that working-memory interventions fail to produce far-transfer effects. However, these reviews were mostly based on studies of children with TD ,25,26,27How might we account for the positive near and far-transfer effects of this intervention? Face-to-face delivery was used on the grounds that social engagement may increase children’s motivation and focused attention to input, providing favourable conditions for take-up of the training. This may be particularly important for the executive-load element of EWM tasks that the trained group received, differentiating this from the judgement subtasks that the active control group received. Indeed, children in the present study enjoyed taking part, all willingly completing the 18 sessions, and children in the trained group were keen to improve their previous score in both tasks, in effect competing with themselves. However, far transfer to language performance has also been observed in recent studies using computer-based training that, like the present training, appears to turn relatively pure working-memory tasks into engaging activities ,39. ThisThe effect of group on performance both post-intervention and nine months later indicates that the EWM element was the active ingredient in the intervention, since the active control group experienced the same input and judgement task as the working-memory training group but without the executive load that also required recall of the final word in each sentence  or location of the ‘odd one out’ . This outcome is in line with the prediction that an EWM training would benefit language comprehension on the grounds that both cognitive activities require simultaneous processing and storage of information ,47. In sIt is notable that the other measure of far transfer to language comprehension , did noThe attribution of gains in Sentence Comprehension to improved EWM is in line with the account of training-induced changes in working memory put forward by Gathercole et al. in a systematic review of working-memory training effects . AccordiOn Gathercole’s  account,What are the wider implications of the view that EWM interventions effect change in executive control of information processing that may benefit performance on language comprehension and also non-executive working-memory tasks? Consider everyday verbal inputs that children receive, for example, a sequence of verbal instructions from a teacher, or someone recounting an event or experience. Such inputs are rapid and transitory so must be processed and interpreted ‘online’. Comprehension therefore relies on immediate verbal STM and language processing, both drawing on established language knowledge. If the training has enabled children to deploy their STM capacity more effectively, as suggested above, this may extend the amount of verbal input they can process and recognise and thereby optimise the deployment of their language knowledge in online comprehension. If the training has enhanced their capacity to store and process information simultaneously, as suggested by gains on the executive working-memory tasks, this may support better retention of processed input while processing subsequent input and thereby improve their comprehension of stretches of verbal discourse. It should particularly benefit activities that do not involve rapid and transitory input, for example, reading comprehension and school-based learning that requires close attention to and the integration of new pieces of information.Having reported the positive outcomes of this study, it is important to acknowledge its limitations. Most notably, due to resource limitations, the sample size was moderate, and the researcher who delivered the training also administered all the assessments so was not blind to the child’s group. This may have led to researcher bias, resulting in more favourable outcomes for the trained group. It is worth pointing out that outcomes in this group varied, and that some children showed little improvement. Nevertheless, replication of the study with larger samples and blinded assessment is needed to preclude possible bias. Further research is also needed to investigate whether there are wider benefits for language performance, of the sort proposed above, in the short and longer term.Working-memory training that targeted executive working-memory skills was found to have far, near, and direct transfer effects in children with developmental language disorder, not only immediately post-intervention but also nine months later. This indicates its potential as an intervention to improve working memory and language comprehension in these children. The intervention programme involved short sessions over a short period, causing little disruption in the school day, and children enjoyed the activities. The programme is relatively straightforward to administer and could be delivered by trained teaching support staff. The findings from this study invite independent evaluation with blind assessment and further research to throw more light on which children benefit, which language and other skills show immediate benefit, and whether benefits are sustained in the even longer-term.


The present study aimed to determine the impact of vitamin D supplementation (VDs) on recovery delay among COVID-19 patients.We performed a randomized controlled clinical trial at the national COVID-19 containment center in Monastir (Tunisia), from May to August 2020. Simple randomization was done in a 1:1 allocation ratio. We included patients aged more than 18 years who had confirmed reverse transcription-polymerase chain reaction (RT-PCR) and who remained positive on the 14th day. The intervention group received VDs ; the control group received a placebo treatment ). We measured the recovery delay and the cycle threshold (Ct) values in RT-PCR for the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The log-rank test and hazard ratios (HR) were calculated.p=0.010). HR was 1.58 . Ct values revealed a stable trend over time in both groups.A total of 117 patients were enrolled. The mean age was 42.7 years (SD 14). Males represented 55.6%. The median duration of viral RNA conversion was 37 days : 29–45.50) in the intervention group and 28 days (95% CI: 23–39) in the placebo group (VDs was not associated with a shortened recovery delay when given to patients for whom the RT-PCR remained positive on the 14th day.NCT04883203.This study was approved by the Human Subjects Protection Tunisia center (TN2020-NAT-INS-40) on April 28, 2020, and by ClinicalTrial.gov on May 12, 2021 with approval number ClinicalTrials.gov ID:  Coronavirus disease 2019 (COVID-19) represents an emerging respiratory infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) . Then, iThe present manuscript was conducted according to the guidelines of the Consolidated Standards of Reporting Trials (CONSORTChecklist2010) .We performed a randomized controlled, parallel-group, blinded, clinical trial.We included patients older than 18 years who had confirmed COVID-19, with a positive RT-PCR, and for whom the RT-PCR remained positive on the 14th day. Participants were consecutively recruited according to laboratory results (COVID-19 positive on the 14th day). We did not include pregnant women and patients who refused to participate.Intervention and data collection were performed in the national center for COVID-19 confinement. From May to August 2020, this center included all Tunisian patients having COVID-19.At the beginning of the COVID-19 epidemic in Tunisia and to limit the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) within the population, the health authorities implemented various interventions such as the creation of a national containment center in Monastir on April 4, 2020. This center was a hotel and allocated 150 beds for patients. Each patient detected COVID-19 positive anywhere in Tunisia, he was transferred by a non-medical ambulance and admitted at this center. The national center was managed by a professor of infectious disease, the preventive medicine department, the bacteriology laboratory, and the psychiatry department. Medical residents and nurses have been assigned to ensure the daily follow-up of the patients. A whole block of this hotel was dedicated to the accommodation of medical and paramedical staff. Each patient was confined to his room and it is forbidden to go out. The meals were given for each in his room. The study protocol is described in Fig. The intervention started on May and finished on August 2020. Intervention was made by medical residents. Participants were randomized into two groups (Group A and Group B). The intervention group (Group A) received VDs  oral form), while the control group (Group B) received a placebo treatment  oral form). After agreement, medical residents administered the treatment according to group allocation of patients. The containers of the drinkable ampoules containing the vitamin D or the placebo treatment were similar. The treatment was distributed in the same day of the RT-PCR results.Our primary outcome measure was the recovery delay defined as the period between the day of the 14th RT-PCR-positive result and the day of the second successive negative RT-PCR test result. Secondary outcomes included the monitoring for the SARS-CoV-2 RT-PCR cycle threshold (Ct) values from the date of randomization until the second successive negative RT-PCR test result. Ct value is inversely correlated to the level of viral ribonucleic acid (RNA) in RT-PCR tests for SARS-CoV-2 . RT-PCR Sample size was calculated using Package “Medcalc” . It was estimated in this survival analysis as 118 patients (59 patients in each group). We considered 80% power, alpha = 0.05, and recovery rate at 21 days of intervention: in group 1, 84%; in group 2, 60% . We accoMicrosoft Excel was used to generate the random allocation sequence . Simple Patients, medical residents, laboratory technicians, and the intervention supervisors were blinded. The groups were labeled as A and B.Data analysis was performed using SPSS Statistics software (SPSS) version 21.0. Statistical analysis was performed using intention-to-treat (ITT) analysis. The Kolmogorov–Smirnov test was used to verify the normal distribution of continuous variables. The mean ± standard deviation (SD) was used to describe the normally distributed data. The median and Inter Quartile Range (IQR) was used to describe the skewed distribution data.χ2 test) or Fisher exact test. Student’s t test was used to compare means for two independent samples. The U-Mann-Whitney test was used to compare the median duration of viral RNA conversion in the VDs and placebo groups, respectively. The negative conversion of viral RNA indicating recovery during the study period, as time-to-event data, was the outcome measure. Survival analysis using the Kaplan-Meier method was performed to compare the recovery delay between the VDs group and the placebo group. The log-rank test and the Kaplan-Meier curve were used to illustrate this comparison. The Cox proportional hazards model was performed to compare the relative effect of the VDs and the placebo on the recovery delay. Results were reported as hazard ratios (HR) with 95% confidence interval (95%CI). One minus the survival function curve was used to show this effect. A HR value >1 would indicate a prolonged recovery delay, whereas an HR < 1 would mean a short recovery delay. Scatter plots and linear regression were used to evaluate the Ct value trends over time in both intervention groups. The slope of the regression line (b) with the standard error (SE) and Pearson’s correlation coefficient (r) was used to describe the Ct value distribution over time. A p value ≤ 0.05 was considered as statistically significant.Frequency rates and percentages were used to present categorical variables. The comparison between frequencies was performed using the chi-square test (This study was approved by the Human Subjects Protection Tunisia center (TN2020-NAT-INS-40) and by ClinicalTrial.gov with the approval number ClinicalTrials.gov ID: NCT04883203. The research ethical considerations were respected including free, informed, written, clear and loyal consent, confidentiality, protection, and assistance.A total of 117 participants were enrolled with 57 patients (48.7%) in the VDs group and 60 (51.3%) in the control group Fig. .Fig. 2Pap=0.047). Regarding symptoms, most of the participants were asymptomatic (65.8%), The most common symptoms were otorhinolaryngological symptoms (12.8%) such as anosmia and ageusia and general signs (12.8%) such as asthenia and headache. Means of Ct values before intervention were equivalent for all subgroups (Table The mean age was 42.7 years SD 14). Males represented 55.6%. The majority of participants (72.64%) had no medical history. The most frequent pre-existing condition was diabetes mellitus (11.96%) followed by asthma and arterial hypertension (6.83% for each one). No significant differences were found between the two groups in all characteristics except for general signs . HR was 1.58  as shown in Fig. The median duration of viral RNA conversion was 37 days (IQR: 29–45.50 days) in intervention group and 28 days (IQR: 23–39 days) in the placebo group (b= 0.028 (SE=0.02), r = 0.172, p=0.164) and control group (b= −0.024 (SE=0.029), r = −0.118, p=0.399). The dispersion of Ct values over time in the two groups is shown in Fig. Monitoring Ct values revealed a stable trend over time in both intervention group (p= 0.76). A second COVID-19 infection after the first episode was noted in 10% of patients assigned to the VDs group and in 0% of patients in the placebo group (p=0.158).At one year of follow-up, persistent COVID-19 symptoms were noted in 34.5% and 38.9.% of patients who received the VDs and the placebo, respectively  [In our study, we analyzed the Ct value which represents the number of replication cycles that are needed during real-time PCR to develop the target sample above a threshold level . The higp=0.02) .The present study presented some limitations. The analysis of vitamin D serum levels was not done. This can be used to identify COVID-19 patients with vitamin D deficiency at baseline. Another limitation of our study was the fact that Ct values were measured on the 14th day following the confirmation of COVID-19 diagnosis for those who were asymptomatic, and on the 7th day after the disappearance of symptoms for pauci-symptomatic ones.According to the study results, vitamin D should not be prescribed to all patients infected by SARS-COV-2. The VDs had not a beneficial effect on recovery delay among COVID-19 patients.


The HL-RE group  trained the first resistance exercise of the contrast sequence with moderate-to-high load (60%–85% 1RM). Before and after the training period, isometric mid-thigh pull (IMTP), squat jump (SJ), counter movement jump (CMJ), and drop-jump (DJ) were performed to evaluate the effect of the intervention on strength and power capacities as primary outcomes. Changes in participants’ anthropometric measures, muscle mass, left and right thigh girth, IMTP relative to bodyweight (IMTP-R), eccentric utilization ratio (EUR), and reactive strength index (RSI) were assessed as secondary outcomes. There was no significant interaction (p > 0.05) between group x time in any power and strength outcome, although SJ and EUR showed a trend to significant interaction . There was an overall effect of time (p < 0.05) in all power and strength variables . There was a significant interaction in muscle mass (MM) , revealing that participants in LL-BFRE increased their muscle mass (6.6 ± 3.1%) compared to HL-RE (3.6 ± 2.0%). Anthropometric variables did not present any group or interaction effect. However, there was a time effect (p < 0.05). Implementing LL-BFRE in place of HL-RE as a conditioning activity in a contrast training sequence might be equally effective in improving lower-body strength and power in preadolescent trampoline gymnasts.To investigate the effects of implementing low-load blood flow restriction exercises (LL-BFRE) instead of high-load exercises (HL-RE) in a contrast training program on strength and power performance of high-level young gymnasts. Fifteen high-level pre-pubescent trampoline gymnasts  were divided into two groups to complete the same structure of a ten-week contrast strength training program differing only in the configuration of the first resistance exercise of the contrast sequence. The LL-BFRE group ( The trampoline gymnasts need high levels of power in their lower limbs to achieve an optimal height in the initial part of a routine and dispose of more aerial time for the functional part to encompass forwards and backward somersaults and twists . ResistaIn this regard, contrast training has been defined as a workout that involves using exercises with loads in a wide range of the force-velocity profile within a sequence, that is, alternating HL and LL exercises set for set . SeveralMeanwhile, even though many studies have reported the effects of training with LL-BFRE on muscular strength and hypertrophy , the eviTherefore, the present work aims to study the effects of LL-BFRE, as a conditioning activity, into a contrast training scheme, on strength and power outcomes in high-level preadolescent trampoline gymnasts.Fifteen preadolescent trampoline gymnasts (seven boys and eight girls) participated in the current study (age: 13.9 ± 0.4 y). All participants were high-level trampoline gymnasts, regional and national junior trampoline team members. Inclusion criteria were: 1) to play the national-level youth competitions finals; 2) to regularly train strength and conditioning, at least two sessions per week, for at least one year; and 3) to be in Tanner Stage II maturation level according to the evaluation of two certified and experienced doctors from Shanghai Sports Bureau. Legal guardians and participants provided informed consent and assent after a thorough explanation of the objectives and scope of the study, including procedures, risks, and benefits. All the procedures complied with ethical standards for research involving human participants set by the Declaration of Helsinki, and the study was approved by the Board of Research Committee of Shanghai Research Institute of Sports Science .http://www.consort-statement.org). Participants were ranked based on maximal isometric strength performance evaluated through the mid-thigh pull test (procedure detailed in testing procedures section) during the testing days pre-intervention and, once paired, were randomly allocated to one of the two experimental. One group, the HL-RE , trained according to a traditional contrast sequence when the first exercise is performed with high-load resistance exercise , the second exercise is performed with a slow stretch-shortening cycle (SSC) exercise  and the last one is a fast SSC exercise . The other group, the LL-BFRE , performed identical contrast sequences and exact exercise only replacing the high-load employed by HL-RE group for low-loads with occlusive cuffs placed on the proximal area of the legs.The present study used a matched pair design with two intervention groups and no control group. This procedure respected the “CONSORT” statement (The participants completed a four-week familiarization period (8 sessions) before the ten-week intervention program . During familiarization sessions, participants spent one hour and a half practicing the strength, power, and plyometric exercises; meanwhile, researchers and coaches instructed the participants about the correct exercises’ technique and safety issues. Additionally, all the participants practiced the testing protocol of strength and power tests and the utilization of the BFR wraps for half an hour every week. Participants recovered at least 48 h before each testing day, before (PRE) and after (POST) the intervention.According to previous recommendations, blood flow restriction was applied on the legs proximally on the femur near the inguinal crease through the individualized perceived pressure method . In ordeWe measured the three-repetition maximum (3RM) test on the back and front squat to prescribe the loads for the first resistance exercise of the contrast training in both groups (for more details see Testing procedures section). After 3RM measurement, the young trampoline gymnasts performed the contrast training shown in 2) were calculated pre- and post-intervention.Testing sessions before and after the intervention were conducted at the same time of the day (before breakfast), the same indoor gym with a similar temperature regulated by air-conditioning (∼26°C). Evaluation sessions were under the supervision of the research team and qualified physicians and coaches. On the morning of the pre-test, two certified and experienced doctors established maturity through the Tanner scale . Then, tIn the afternoon, participants performed a standardized 15 min warm-up  before the power and strength tests. The lower body’s power was assessed using the vertical squat jump test (SJ), the vertical countermovement jump test (CMJ), and the drop jump test from a 30 cm-height box (DJ). Furthermore, the eccentric utilization ratio (EUR) and the reactive strength index (RSI) were calculated from the jump tests (detailed below). Participants performed three maximal voluntary contractions in the isometric mid-thigh pull (IMTP). The exercise testing sequence and rest intervals between repetitions and sets for power and strength tests tried to minimize the accumulated fatigue through the evaluating session. The order within this protocol was constant: 1. SJ, 2. CMJ, 3. DJ, and 4. IMTP. The participants performed three successful repetitions, and they were blinded to the results of every repetition for ensuring the best effort in every repetition. If the last attempt was the highest, the participant performed one extra repetition to avoid possible deviations. The recovery between repetitions was 1 minute in jump tests and 2 minutes in the IMTP test. The power and strength evaluations were performed on a force platform . The jumping height (cm) of SJ, CMJ, and DJ was automatically calculated by Mars . The description of each test and the variable extracted are presented below.The participants started from the static position with knees flexed to 90° and with hands on the hips . After eThe participant stood up-right and still on the force platform for at least one second. After hearing “go” the from tester, participants counter-moved , and then vertically jumped with maximal effort . The hanThe EUR was calculated by dividing the height (cm) reached in the CMJ by the height in the SJ. The EUR has been proposed to indicate SSC performance in various sports and during different training phases The participants stood upright and still on top of the 30 cm height box with their hands on hips. After the signal, they dropped from the box and, after the contact with the platform, jumped vertically with maximal effort . The resThe RSI was calculated by dividing the height jumped by the time in contact with the ground prior to take-off during DJ (cm/seconds). This parameter has been suggested to quantify plyometric or fast SSC performance .−1) was calculated as the force produced regarding the body mass.IMTP was conducted following the protocol recommended by previous studies . In brieAfter testing sessions and aimed to prescribe training loads for the conditioning activity within the contrast sequence, participants accomplished the 3RM test in the last session of the familiarization period. A qualified strength and conditioning coach supervised the test sessions and all the training sessions. A previously recommended protocol was followed . Brieflyhttps://www.jamovi.org/). GAMLj estimates variance components with restricted  maximum likelihood, which, unlike earlier maximum likelihood estimation, produces unbiased estimates of variance and covariance parameters. The intersubject factor group (LL-BFRE and HL-RE), the intrasubject factor time (PRE and POST), and the interaction (Group × Time) were set as fixed effects and participants’ intercepts were set as a random effect. F and t values and the corresponding degrees of freedom were computed. Within-subject changes were evaluated by the β coefficients and their corresponding 95% CI, representing a non-standardized effect size. Mean percentage changes (100 × [Post-Pre] × Pre−1) and standard deviation were calculated for all parameters. Between-group changes were evaluated by the estimated parameter with the 95% CI of the interaction between the fixed effect of the model. The alpha level was set at p < 0.05.Test-retest reliability was reported using the intraclass correlation coefficient (ICC) with 95% confident interval a single-measurement, absolute-agreement, 2-way mixed-effects model. Based on the 95% confident interval (CI) of the ICC estimate, values less than 0.5, between 0.5 and 0.75, between 0.75 and 0.9, and greater than 0.90 were interpreted as poor, moderate, good, and excellent reliability, respectively . Changesp > 0.05) between group x time in any power and strength outcome (p < 0.05) in all power and strength variables .The ICC with 95% CI of the variables were from “good” to “excellent” for CMJ  and DJ ; and from “moderate” to “excellent” for SJ , RSI  and IMTP . There was no significant interaction , and HL-RE improved 3.3 cm  (p = 0.06) and a significant time effect (p < 0.001). In fact, HL-RE increased 14.6 ± 9.4%  and LL-BFRE estimably more, 27.6 ± 15.3%  (p = 0.065) to interaction in EUR. LL-BFRE significant decreased EUR , notwithstanding HL-RE did not change EUR   . On the < 0.001) . Differe= 0.437) . The mea= 0.437) .p = 0.675), but it showed a time effect that analyzed within each group revealed a 3.8 cm DJ improvement in HL-RE , and not changes for LL-BFRE   in HL-RE and 38.4 ± 40.6%  in LL-BFRE (Outcomes in DJ showed a high variability of responses within groups (ICC random intercept = 0.482). DJ did not show interaction effect (= 0.103) . Despite LL-BFRE .13 = 4.74, p < 0.001; and LL-BFRE: β = 118 N, 95% CI = , t13 = 4.00, p = 0.002). The IMTP-R increased similarly in both groups  (We observed a similar mean percentage improvement in IMTP for HL-RE (11.3 ± 8.0%) and LL-BFRE (9.6 ± 4.5%). Moreover, simple effects analysis showed that both groups improved IMTP  .13 = 2.67, p = 0.019), revealing that participants in LL-BFRE increased their muscle mass (6.6 ± 3.1%) compared to HL-RE (3.6 ± 2.0%). The fixed effect omnibus test did not reveal any group or interaction effect in the anthropometric variables. However, there was a time effect on all the variables (p < 0.05). Group simple effects within PRE revealed no significant differences between groups, which ruled out group allocation or initial bias. The simple effects of time within each group are shown in Changes in anthropometric measures and body composition are presented in We found that preadolescent trampoline gymnasts increased their jump height  and strength capabilities (IMTP) regardless of employing HL or blood flow restricted LL as conditioning activity within a contrast training strength program performed two days per week for ten weeks. These results suggest the potential usefulness of BFR with low loads as a conditioning activity in a contrast training sequence in preadolescents athletes. However, our results must be interpreted with caution since we could not have a group that only trained specific trampoline sessions and thus compare the magnitude of change between the two interventions group with a control group. Participants’ allocation was based on the rank obtained from the maximal isometric mid-thigh pull test in the pre-intervention to prevent participants’ force level from influencing the present study’s independent variable . Moreover, the groups did not significantly differ in any jump measures  in the PRE, meaning that post-training differences could not be attributed to unequal group composition or pre-experimental biases.The present work is the first investigation to study the effects of contrast-type resistance exercise training on the performance of high-level early adolescent trampoline gymnasts. The increments observed CMJ (HL-RE: 12.4 ± 5.4% and LL-BFRE: 17.2 ± 8.7%) and SJ (HL-RE: 14.6 ± 9.4% and LL-BFRE: 27.6 ± 15.3%) in both groups were much higher than those reported in the literature for pubertal volleyball players when trained with plyometrics (CMJ: 3.4% and SJ: 4.1%) or combining resistance and plyometric exercises (CMJ: 6.3% and SJ: 7.1%) . In the Trampoline athletes in LL-BFRE improved more SJ than CMJ , contrasting to HL-RE that experimented a similar improvement in both exercises . SJ and CMJ performance depends on common factors related to changes in muscle structure  and neurAs aforementioned, trampoline athletes in LL-BFRE gained more muscle mass than those in HL-RE . The result of our study is consistent with the evidence from other previous studies employing BFR with young adult populations . FurtherOn the other hand, the current study demonstrated that a contrast training program using low-loads with BFR as a conditioning activity might provide an effective and equivalent positive influence on maximal strength compared to using high-loads for preadolescents athletes. Our results agree with the evidence from other previous studies employing low load BFR with other populations  and high2+ released by the sarcoplasmic reticulum due to phosphorylation of the regulatory light chain of myosin) caused by a precedent conditioning activity is the cause of improved performance in high-speed strength or power exercises during a session , but simple effects showed an increment in the HL-RE and no changes in LL-BFRE. As shown in Our study was not without limitations. Small sample size and the absence of a control group training only specific sessions must be addressed in future investigations. Furthermore, a study design with bigger samples with higher representation by sex is warranted to understand better sex differences in adaptations to LL-BFRE in power and strength training. Lastly, electrophysiologic measures to analyze motor unit recruitment and firing rate and changes in tendon-muscle architecture can give valuable information about the origin of the adaptations to training with LL-BFRE as a conditioning activity within a contrast training sequence.Low-intensity resistance training with BFR could be implemented into an integrated strength training program with a combination of power or plyometric exercise to effectively improve the strength and jump height performance in lower limbs in preadolescent athletic populations. Our study has provided valuable implications for coaches working with elite young athletes, especially when using high loads in a contrast training structure is not possible.Implementing LL-BFRE in place of HL-RE in a contrast training structure is safe and might be equally effective in improving lower-body strength and power in preadolescent trampoline gymnasts.